RyanNg

RyanNg

Cipher is an opensource memory layer specifically designed for coding agents. Compatible with Cursor, Windsurf, Claude Desktop, Claude Code, Gemini CLI, AWS's Kiro, VS Code, and Roo Code through MCP, and coding agents, such as Kimi K2.

Category
Visit Server

README

Cipher

<div align="center">

<img src="./assets/cipher-logo.png" alt="Cipher Agent Logo" width="400" />

<p align="center"> <em>Memory-powered AI agent framework with MCP integration</em> </p>

<p align="center"> <a href="LICENSE"><img src="https://img.shields.io/badge/License-Elastic%202.0-blue.svg" alt="License" /></a> <img src="https://img.shields.io/badge/Status-Beta-orange.svg" alt="Beta" /> <a href="https://docs.byterover.dev/cipher/overview"><img src="https://img.shields.io/badge/Docs-Documentation-green.svg" alt="Documentation" /></a> <a href="https://discord.com/invite/UMRrpNjh5W"><img src="https://img.shields.io/badge/Discord-Join%20Community-7289da" alt="Discord" /></a> </p>

</div>

<div align="center"> <a href="https://www.producthunt.com/products/byterover?embed=true&utm_source=badge-top-post-badge&utm_medium=badge&utm_source=badge-cipher-by-byterover" target="_blank"> <img src="https://api.producthunt.com/widgets/embed-image/v1/top-post-badge.svg?post_id=1000588&theme=light&period=daily&t=1754744170741" alt="Cipher by Byterover - Open-source, shared memory for coding agents | Product Hunt" style="width: 250px; height: 54px;" width="250" height="54" /> </a> </div>

Overview

Cipher is an opensource memory layer specifically designed for coding agents. Compatible with Cursor, Windsurf, Claude Desktop, Claude Code, Gemini CLI, AWS's Kiro, VS Code, and Roo Code through MCP, and coding agents, such as Kimi K2. (see more on examples)

Built by Byterover team

Key Features:

  • 🔌 MCP integration with any IDE you want.
  • 🧠 Auto-generate AI coding memories that scale with your codebase.
  • 🔄 Switch seamlessly between IDEs without losing memory and context.
  • 🤝 Easily share coding memories across your dev team in real time.
  • 🧬 Dual Memory Layer that captures System 1 (Programming Concepts & Business Logic & Past Interaction) and System 2 (reasoning steps of the model when generating code).
  • ⚙️ Install on your IDE with zero configuration needed.

Quick Start 🚀

NPM Package (Recommended for Most Users)

# Install globally
npm install -g @byterover/cipher

# Or install locally in your project
npm install @byterover/cipher

Docker

<details> <summary>Show Docker Setup</summary>

# Clone and setup
git clone https://github.com/campfirein/cipher.git
cd cipher

# Configure environment
cp .env.example .env
# Edit .env with your API keys

# Start with Docker
docker-compose up --build -d

# Test
curl http://localhost:3000/health

💡 Note: Docker builds automatically skip the UI build step to avoid ARM64 compatibility issues with lightningcss. The UI is not included in the Docker image by default.

To include the UI in the Docker build, use: docker build --build-arg BUILD_UI=true .

</details>

From Source

pnpm i && pnpm run build && npm link

CLI Usage 💻

<details> <summary>Show CLI commands</summary>

# Interactive mode
cipher

# One-shot command
cipher "Add this to memory as common causes of 'CORS error' in local dev with Vite + Express."

# API server mode
cipher --mode api

# MCP server mode
cipher --mode mcp

# Web UI mode
cipher --mode ui

⚠️ Note: When running MCP mode in terminal/shell, export all environment variables as Cipher won't read from .env file.

💡 Tip: CLI mode automatically continues or creates the "default" session. Use /session new <session-name> to start a fresh session.

</details>

Cipher Web UI

The Cipher Web UI provides an intuitive interface for interacting with memory-powered AI agents, featuring session management, tool integration, and real-time chat capabilities.

Configuration

Cipher supports multiple configuration options for different deployment scenarios. The main configuration file is located at memAgent/cipher.yml.

Basic Configuration ⚙️

<details> <summary>Show YAML example</summary>

# LLM Configuration
llm:
  provider: openai # openai, anthropic, openrouter, ollama, qwen
  model: gpt-4-turbo
  apiKey: $OPENAI_API_KEY

# System Prompt
systemPrompt: 'You are a helpful AI assistant with memory capabilities.'

# MCP Servers (optional)
mcpServers:
  filesystem:
    type: stdio
    command: npx
    args: ['-y', '@modelcontextprotocol/server-filesystem', '.']

</details>

📖 See Configuration Guide for complete details.

Environment Variables 🔐

Create a .env file in your project root with these essential variables:

<details> <summary>Show .env template</summary>

# ====================
# API Keys (At least one required)
# ====================
OPENAI_API_KEY=sk-your-openai-api-key
ANTHROPIC_API_KEY=sk-ant-your-anthropic-key
GEMINI_API_KEY=your-gemini-api-key
QWEN_API_KEY=your-qwen-api-key

# ====================
# Vector Store (Optional - defaults to in-memory)
# ====================
VECTOR_STORE_TYPE=qdrant  # qdrant, milvus, or in-memory
VECTOR_STORE_URL=https://your-cluster.qdrant.io
VECTOR_STORE_API_KEY=your-qdrant-api-key

# ====================
# Chat History (Optional - defaults to SQLite)
# ====================
CIPHER_PG_URL=postgresql://user:pass@localhost:5432/cipher_db

# ====================
# Workspace Memory (Optional)
# ====================
USE_WORKSPACE_MEMORY=true
WORKSPACE_VECTOR_STORE_COLLECTION=workspace_memory

# ====================
# AWS Bedrock (Optional)
# ====================
AWS_ACCESS_KEY_ID=your-aws-access-key
AWS_SECRET_ACCESS_KEY=your-aws-secret-key
AWS_DEFAULT_REGION=us-east-1

# ====================
# Advanced Options (Optional)
# ====================
# Logging and debugging
CIPHER_LOG_LEVEL=info  # error, warn, info, debug, silly
REDACT_SECRETS=true

# Vector store configuration
VECTOR_STORE_DIMENSION=1536
VECTOR_STORE_DISTANCE=Cosine  # Cosine, Euclidean, Dot, Manhattan
VECTOR_STORE_MAX_VECTORS=10000

# Memory search configuration
SEARCH_MEMORY_TYPE=knowledge  # knowledge, reflection, both (default: knowledge)
DISABLE_REFLECTION_MEMORY=true  # default: true

💡 Tip: Copy .env.example to .env and fill in your values:

cp .env.example .env

</details>

MCP Server Usage

Cipher can run as an MCP (Model Context Protocol) server, allowing integration with MCP-compatible clients like Claude Desktop, Cursor, Windsurf, and other AI coding assistants.

Quick Setup

To use Cipher as an MCP server in your MCP client configuration:

{
	"mcpServers": {
		"cipher": {
			"type": "stdio",
			"command": "cipher",
			"args": ["--mode", "mcp"],
			"env": {
				"MCP_SERVER_MODE": "aggregator",
				"OPENAI_API_KEY": "your_openai_api_key",
				"ANTHROPIC_API_KEY": "your_anthropic_api_key"
			}
		}
	}
}

📖 See MCP Integration Guide for complete MCP setup and advanced features.

👉 Built‑in tools overview — expand the dropdown below to scan everything at a glance. For full details, see docs/builtin-tools.md 📘.

<details> <summary>Built-in Tools (overview)</summary>

  • Memory
    • cipher_extract_and_operate_memory: Extracts knowledge and applies ADD/UPDATE/DELETE in one step
    • cipher_memory_search: Semantic search over stored knowledge
    • cipher_store_reasoning_memory: Store high-quality reasoning traces
  • Reasoning (Reflection)
    • cipher_extract_reasoning_steps (internal): Extract structured reasoning steps
    • cipher_evaluate_reasoning (internal): Evaluate reasoning quality and suggest improvements
    • cipher_search_reasoning_patterns: Search reflection memory for patterns
  • Workspace Memory (team)
    • cipher_workspace_search: Search team/project workspace memory
    • cipher_workspace_store: Background capture of team/project signals
  • Knowledge Graph
    • cipher_add_node, cipher_update_node, cipher_delete_node, cipher_add_edge
    • cipher_search_graph, cipher_enhanced_search, cipher_get_neighbors
    • cipher_extract_entities, cipher_query_graph, cipher_relationship_manager
  • System
    • cipher_bash: Execute bash commands (one-off or persistent)

</details>

Tutorial Video: Claude Code with Cipher MCP

Watch our comprehensive tutorial on how to integrate Cipher with Claude Code through MCP for enhanced coding assistance with persistent memory:

Cipher + Claude Code Tutorial

Click the image above to watch the tutorial on YouTube.

For detailed configuration instructions, see the CLI Coding Agents guide.

Documentation

📚 Complete Documentation

Topic Description
Configuration Complete configuration guide including agent setup, embeddings, and vector stores
LLM Providers Detailed setup for OpenAI, Anthropic, AWS, Azure, Qwen, Ollama, LM Studio
Embedding Configuration Embedding providers, fallback logic, and troubleshooting
Vector Stores Qdrant, Milvus, In-Memory vector database configurations
Chat History PostgreSQL, SQLite session storage and management
CLI Reference Complete command-line interface documentation
MCP Integration Advanced MCP server setup, aggregator mode, and IDE integrations
Workspace Memory Team-aware memory system for collaborative development
Examples Real-world integration examples and use cases

🚀 Next Steps

For detailed documentation, visit:

Contributing

We welcome contributions! Refer to our Contributing Guide for more details.

Community & Support

cipher is the opensource version of the agentic memory of byterover which is built and maintained by the byterover team.

  • Join our Discord to share projects, ask questions, or just say hi!
  • If you enjoy cipher, please give us a ⭐ on GitHub—it helps a lot!
  • Follow @kevinnguyendn on X

Contributors

Thanks to all these amazing people for contributing to cipher!

Contributors

MseeP.ai Security Assessment Badge

MseeP.ai Security Assessment Badge

Star History

<a href="https://star-history.com/#campfirein/cipher&Date"> <img width="500" alt="Star History Chart" src="https://api.star-history.com/svg?repos=campfirein/cipher&type=Date&v=2"> </a>

License

Elastic License 2.0. See LICENSE for full terms.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured